GPT-5.6-sol Agent

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context by stating 'does not run the model and does not require a bearer token,' which clarifies authentication requirements and confirms the absence of side effects beyond what annotations imply.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, focused sentence that immediately states the return value and key behavioral traits. It contains no filler or repetition, and every clause adds meaningful information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no parameters, no output schema, and clear annotations, the description supplies all necessary information: what it returns, that it is metadata-only, and that no token is needed. It is fully complete for an agent to decide when to call this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the baseline is 4. The description enumerates the return fields (identity, price, endpoint, URL), which helps the agent understand the tool's output, and there are no parameters that need additional explanation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool 'Returns this agent's identity, listed per-task price, MCP endpoint, and access URL,' using a specific verb and resource. It is distinct from sibling tools that all deal with run lifecycle (create_run, get_run_result, get_run_status).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context: it is a metadata call that does not execute the model and requires no bearer token, implying it is for pre-run configuration or informational purposes. It does not explicitly name alternatives, but the sibling set makes the distinction obvious.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses that the task is asynchronous and 'can consume paid model capacity,' adding important behavioral context beyond the annotations. The annotations indicate readOnlyHint=false, confirming this is a write operation, and the description's 'queues' aligns with that. It does not mention rate limits or failure modes, but the cost warning is valuable.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise—two sentences—with the action first, followed by a warning about cost and then the next steps. Every sentence carries meaningful content with no filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the action, async behavior, cost, and follow-up workflow, but it does not state what the tool returns (e.g., a run ID) which is necessary to use the suggested status/result tools. Since there is no output schema, this missing information leaves a gap. The description could be more complete by mentioning the response payload.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already provides 100% coverage with descriptions for both parameters ('task' and 'task_input'), so the description adds little parameter-specific meaning. It indirectly references the 'task' parameter by saying 'Queues an authenticated asynchronous task,' but no additional syntax or format details beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's primary action: 'Queues an authenticated asynchronous task.' This distinguishes it from sibling tools like agentfarm_get_run_status and agentfarm_get_run_result, which are for polling and reading results. The title reinforces the purpose as 'Create a GPT-5.6-sol Agent run,' providing a specific verb and resource.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidance by describing the workflow: 'Poll with agentfarm_get_run_status, then read agentfarm_get_run_result.' This tells the agent when to use this tool (to start a run) and what to do next, clearly differentiating it from the read/status siblings. It does not explicitly mention agentfarm_agent_info, but the complementary nature of the siblings is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds the 'authenticated' prerequisite and specifies that it returns final summary and artifact URLs, which gives useful context about what the tool does beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence with no filler or redundant information. It is front-loaded with the primary action and immediately states the output.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple get-style tool with one parameter and strong annotations, the description adequately covers the return content. It does not explain error handling or prerequisites beyond 'authenticated', but these are not critical given the tool's simplicity and the absent output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already describes run_id as 'AgentFarm run identifier' with 100% coverage. The description does not add additional parameter details, so it meets the baseline but does not exceed it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Returns') and names the resource ('final summary and artifact download URLs') for an authenticated run. It clearly distinguishes this from sibling tools like agentfarm_get_run_status by focusing on the final result rather than status.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'for an authenticated run' provides clear context that this tool is used after a run has been executed and requires authentication. It does not explicitly name alternatives or exclusions, but the distinction from sibling tools is implicit through the 'final' wording.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the core safety profile is covered. The description adds the 'authenticated run' requirement, which is not in the annotations, and lists the specific status values returned, providing meaningful context beyond structured metadata.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence that front-loads the key information (what it returns) and specifies the exact statuses. Every word adds value, with no redundancy or irrelevant detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read-only status-checking tool with one parameter, good annotations, and no output schema, the description fully covers what the agent needs: it clarifies the run status values and the authentication requirement. Nothing critical is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema covers the single parameter run_id with a clear description ('AgentFarm run identifier'), achieving 100% schema description coverage. The tool description does not add additional parameter semantics, so it does not exceed the baseline set by the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Returns') and the resource ('status for an authenticated run'), enumerating the possible values (queued, running, succeeded, failed). This distinguishes it from sibling tools like agentfarm_get_run_result (which likely retrieves run data) and agentfarm_create_run (which creates runs).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for checking run status, but it does not explicitly say when to use this tool versus alternatives like get_run_result or get_run_info. No exclusion criteria or scenario guidance is provided, making it adequate but not highly instructive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.